A new tool, based in part upon MP3 audio coding, could alleviate the problem

BUFFALO, N.Y. — The failure of hospital caregivers to
respond to medical alerts is often attributed to “alarm
fatigue” — the idea that nurses or doctors can become
desensitized to the nonstop cacophony of beeps that
patient-monitoring devices make.

A growing field of research suggests another possible
explanation: alarms sounding simultaneously can blend together,
making one or more of them inaudible. The phenomenon, known as
masking, can make it difficult for caregivers to differentiate
alarms, including those that signal life-threatening
emergencies.

Now, a University at Buffalo-led research team is developing a
computer-based tool — using the same principles as MP3 audio
files — to identify these auditory blind spots. The effort,
which is funded by a $750,000 U.S. Department of Health and Human
Services grant, may help reduce preventable deaths associated with
alarm system failures.

“It’s an important but understudied problem. When
you have a hodgepodge of different machines from different vendors,
everything is sort of thrown together without much thought given to
the coordination of them,” says Matthew Bolton, PhD,
assistant professor of industrial and systems engineering at UB,
and the study’s lead author.

An example of alarm masking:

Patient-monitoring alarms help caregivers perform their jobs.
However, too many alarms can be problematic. According to the Joint
Commission, a nonprofit that accredits hospitals, one patient can
trigger hundreds of alarms each day. This corresponds to thousands
of alarms daily from a single unit, and tens of thousands
hospital-wide each day.

All the alerts can lead to alarm fatigue, which along with other
alarm system failures were linked to 138 reported deaths between
2010 and June 2015, according to the Joint Commission.

Because “alarm masking is an extremely challenging problem
to identify,” Bolton says, it is unclear how many of those
alarms went unanswered because the sound from another alarm
rendered it inaudible. But the Joint Commission has acknowledged
that individual alarm signals can be difficult to detect, and that
this phenomenon is at least partially responsible for the patient
safety problems associated with medical alarms.

The problem of alarm masking is exacerbated by the excessive
number of alarms, and because alarms are often melodies of tonal
sounds, which easily mask each other, Bolton says.

Tapping into MP3 code

To address the problem, Bolton researched the science behind
audio file formats. Among those he examined was MP3, the popular
audio coding format launched in the 1990s, which uses sophisticated
models of human hearing to compress audio data by removing sounds
that are masked.

Bolton combined these human hearing models with model checking
(an automated, computational approach for finding problems in
complex systems) to assess masking in a common patient-monitoring
device with six different alarms.

He found that each alarm could be at least partially masked when
other alarms went off simultaneously, and that one high-priority
alarm could be completely masked.

“It’s distressing because this is only one
machine,” Bolton says.

Future plans

Analyzing an alarm system, such as the one described above, can
take days. However, Bolton is refining the method to shorten that
time period; it now takes roughly 20 minutes to run a typical alarm
system masking audit, he said.

The effort is supported by Health and Human Services, which
awarded the three-year, $750,000 grant through the Agency for
Healthcare Research and Quality. Bolton will use the tool to
analyze and make recommendations for improving the international
medical alarm standard (IEC 60601-1-8).

He is working with the Association for the Advancement of
Medical Instrumentation (AAMI) Foundation, which is responsible for
revising the standards for alarm sounds to reduce masking.